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ERIC Number: EJ1061231
Record Type: Journal
Publication Date: 2015-Jun
Pages: 30
Abstractor: As Provided
Reference Count: 27
ISSN: ISSN-0013-1644
Type I and Type II Error Rates and Overall Accuracy of the Revised Parallel Analysis Method for Determining the Number of Factors
Green, Samuel B.; Thompson, Marilyn S.; Levy, Roy; Lo, Wen-Juo
Educational and Psychological Measurement, v75 n3 p428-457 Jun 2015
Traditional parallel analysis (T-PA) estimates the number of factors by sequentially comparing sample eigenvalues with eigenvalues for randomly generated data. Revised parallel analysis (R-PA) sequentially compares the "k"th eigenvalue for sample data to the "k"th eigenvalue for generated data sets, conditioned on"k"- 1 underlying factors. T-PA and R-PA are conceptualized as stepwise hypothesis-testing procedures and, thus, are alternatives to sequential likelihood ratio test (LRT) methods. We assessed the accuracy of T-PA, R-PA, and LRT methods using a Monte Carlo approach. Although no method was uniformly more accurate across all 180 conditions, the PA approaches outperformed LRT methods overall. Relative to T-PA, R-PA tended to perform better within the framework of hypothesis testing and to evidence greater accuracy in conditions with higher factor loadings.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A